BMS5310 AI integrated proteomics and protein design

In this unit you will explore proteomics as a discipline of biological inference rather than simple protein cataloguing. You will develop a conceptual framework by contrasting proteomics with genomics and transcriptomics, and by examining challenges such as dynamic range, post-translational modifications, and proteoforms. You will learn the principles of protein chemistry and mass spectrometry, including how peptides are generated, detected, and computationally interpreted.

Through guided analysis of real datasets, you will perform peptide identification, protein inference, and quantitative analysis, with emphasis on false discovery control, ambiguity, and probabilistic reasoning. You will design proteomics workflows and evaluate how experimental choices shape downstream statistical and biological conclusions.

You will apply statistical and computational approaches to interpret proteomics data at functional and systems levels, and use these insights to generate and test biological hypotheses. You will also compare data-driven and physics-based approaches to protein structure prediction and design, and apply modern tools to biological and engineering problems.

Throughout the unit, you will engage in critical discussion of limitations, reproducibility, and responsible scientific interpretation, alongside emerging areas such as AI-assisted protein design.